Have you ever wondered how decisions about road networks, traffic flow, and public transit are made? This presentation aims to give you an accessible, yet in-depth, look at the cutting-edge ways we’re using big data to revolutionize traffic engineering and planning. Specifically, we’ll focus on a powerful technique known as multi-resolution modeling, which allows engineers to analyze traffic at various levels—from an individual intersection to a whole city or region.
In traditional traffic planning, data could be scarce and models sometimes had limitations. But in today’s big data era, we have access to an unprecedented amount of information—from GPS trackers, road sensors, and even social media—that can enrich these models. This enables engineers and planners to better understand traffic patterns, congestion, and infrastructure needs at multiple scales.
The real magic happens when we use big data to inform multi-resolution models. Imagine being able to tweak a model in real-time based on current traffic data, thereby predicting the impact of a new traffic signal or road closure within minutes! This type of dynamic modeling is not just a technical advancement; it’s a game-changer for decision-makers who can now make quicker, smarter, and more informed choices about transportation.
We’ll explore some real-world examples and discuss how this technology is already helping cities become more efficient and responsive to the needs of their residents. Whether you’re interested in engineering, urban planning, or the role of technology in society, this talk will give you a glimpse into the future of smart, data-driven transportation solutions.
Joseph “JJ” Samus Jr. is a senior engineer, planner, and project manager specializing in transportation planning and traffic engineering for federal, state, and municipal clients. A published traffic professional, JJ has provided detailed traffic development and operational analysis throughout his career in urban and regional planning, project management, and a variety of production tasks, including application and development of travel demand models (TDM) and reports; corridor operational analysis; traffic development and forecasting; multi-resolution modeling (MRM) application; performing Interchange Access Requests (IMRs, IJRs, IOARs); developing a wide range of studies including Project Development and Environment (PD&E), planning, traffic, managed lanes, and detailed corridor simulations. Leading a diverse team, JJ has pioneered the application of ‘Big Data’ on urban and regional transportation planning efforts and has made it an integral part of his team’s multi-resolution approach and process to project analysis.